Wathieu Henri, Issa Naiem T, Byers Stephen W, Dakshanamurthy Sivanesan
Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington DC, 20057 USA.
Curr Pharm Des. 2016;22(21):3097-108. doi: 10.2174/1381612822666160224141930.
The ascent of polypharmacology in drug development has many implications for disease therapy, most notably in the efforts of drug discovery, drug repositioning, precision medicine and combination therapy. The single- target approach to drug development has encountered difficulties in predicting drugs that are both clinically efficacious and avoid toxicity. By contrast, polypharmacology offers the possibility of a controlled distribution of effects on a biological system. This review addresses possibilities and bottlenecks in the efficient computational application of polypharmacology. The two major areas we address are the discovery and prediction of multiple protein targets using the tools of computer-aided drug design, and the use of these protein targets in predicting therapeutic potential in the context of biological networks. The successful application of polypharmacology to systems biology and pharmacology has the potential to markedly accelerate the pace of development of novel therapies for multiple diseases, and has implications for the intellectual property landscape, likely requiring targeted changes in patent law.
多药理学在药物研发中的兴起对疾病治疗具有诸多影响，在药物发现、药物重新定位、精准医学和联合治疗等方面尤为显著。药物研发的单靶点方法在预测临床有效且无毒性的药物时遇到了困难。相比之下，多药理学为在生物系统中实现可控的效应分布提供了可能。本综述探讨了多药理学高效计算应用中的可能性和瓶颈。我们探讨的两个主要领域是利用计算机辅助药物设计工具发现和预测多个蛋白质靶点，以及在生物网络背景下利用这些蛋白质靶点预测治疗潜力。多药理学在系统生物学和药理学中的成功应用有可能显著加快多种疾病新疗法的研发速度，并对知识产权格局产生影响，可能需要对专利法进行针对性修改。
